Two related projects: RDA and microarray analysis summarized in abstract form below: RDA: Gene isolation methods used during positional cloning rely on physical contigs consisting of bacterial artificial chromosomes, P1 or cosmid clones. However, in most instances, the initial framework for physical mapping consists of contigs of yeast artificial chromosome (YACs), large vectors which are suboptimal substrates for gene isolation. Here we report a strategy to identify gene sequences contained within a YAC by using cDNA representational difference analysis (RDA) to directly isolate transcripts expressed from the YAC in mammalian cells. The RDA tester cDNAs were generated from a previously reported hamster cell line derived by stable transfer of a 590 kb YAC (911D5) which expressed NPC1, the human gene responsible for Niemann-Pick type C (NP-C). The driver cDNAs were generated from a control hamster cell line which did not contain the YAC that expressed NPC1. Among the gene fragments obtained by RDA, NPC1 was the most abundant product. In addition, two non-NPC1 fragments were isolated which were mapped to and expressed from 911D5. One of these RDA gene fragments (7-R) spans more than one exon and has 98% sequence identity with a human cDNA clone previously reported as an expressed sequence tag (EST), but not mapped to a chromosomal region. The other fragment (2-R) which had no significant sequence similarities with known mammalian genes or ESTs, was further localized to the region of overlap between YACs 911D5 and 844E3. The latter YAC is part of a contig across the NP-C candidate region, but does not contain NPC1. This two part approach in which stable YAC transfer is followed by cDNA RDA should be a useful adjunct strategy to expedite the cloning of human genes when a YAC contig is available across a candidate interval. Microarray analysis: A major obstacle in positional cloning is identifying a mutated gene within a large physical contig, potentially containing hundreds of candidate genes. Here we describe a novel use of DNA microarray technology to identify: (1) exons within a large defined genomic expanse, without a priori sequence data and (2) a disease gene which has been physically mapped to a specific genomic region. The feasibility of the approach was tested using resources obtained during the positional cloning of the gene responsible for Neimann-Pick Type C (NP-C) disease (NPC1). First, to identify NPC1 exons, an array was generated from genomic fragments of a 110 kb bacterial artificial chromosome (BAC), 108N2, which spans NPC1. Fluorescently labeled NPC1 cDNA clearly identified a series of genomic fragments on the BAC array, which contained NPC1 exons. Many of these NPC1 exons also contained intronic sequences and were used to determine part of the genomic structure of NPC1. Second, to prove NPC1 could be identified based upon differential gene expression in mammalian cells, sub-arrays of genomic fragments from 108N2 were hybridized with fluorescently labeled transcripts (cDNAs). The cDNAs were generated from the hamster cell line CT60 (NP-C phenotype), and a cell line derived from CT60 (normal phenotype with respect to NP-C) by stable transduction of a 590 kb yeast artificial chromosome (YAC) containing NPC1 and encompassing 108N2. The cDNA from the normal, non-NP-C cell line detected NPC1 exons, whereas no NPC1 exons or other genomic fragments from 108N2 were detected using CT60 cDNA. Thus, the array technology correctly identified NPC1 based on a physical contig and differential NPC1 mRNA levels between NP-C and non-NP-C cells. This technique should enable rapid disease gene identification when a physical contig exists for the region of interest and subtle mutations, including small deletions, insertions, and exon skipping, result in changes in message level at regions of the transcript.